Month September 2012

James Allworth, Harvard Business School Forum for Growth and Innovation fellow and co-author of How Will You Measure Your Life joins Horace for an in-depth discussion of the vulnerability of Apple to low-end disruption. Specifically, assuming the iPhone reaches a point of over-service, did Apple arm its suppliers with the means to create its replacement? We dip into case studies of Dell, HP, HTC and Microsoft and touch on how iPod escaped this fate.

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Once you’re ready to work with the note, Scratch gives you the options you need to move the text where it belongs: Dropbox, email, your favorite text editor or just about anywhere else.

Tim Cook is quoted as having said the inventory is not only evil but that it’s fundamentally evil.

With just-in-time production inventory can be reduced, at least work-in-progress inventory. Unfortunately inventory cannot be completely eliminated. The fact remains that you sometimes need to stockpile product for launch and need to have some on hand depending which way it’s sold. There is also substantial channel inventory (which is off Apple’s books but still evil) that needs to be in the hands of distributors.

Tight inventory management has become a characteristic of Apple and that contributes to getting ranked number one in Supply Chain Management. So we can expect that Apple runs a tight ship. In fact we have evidence of this through the ability to track our purchases from when they ship out of a factory in China all the way to our homes.

This tracking in itself shows that when product is in high demand production is initiated on direct consumer orders not just in response to maintaining a level of inventory. So with that in mind, we can revisit the question of how many iPhones 5 the company has produced.

First, we need to step back and recall the method for analyzing production. I built a model which attempts to show what a typical production run for an iPhone model would look like. I first published the process in early 2011. It used the historic data from iPhone 1, 3G and 3GS to try to predict iPhone 4 production. I’ve updated the model to show what that would look like today.

When Apple announced five million iPhone 5 were sold to end users over its launch weekend, I was surprised. Not because my guess had been around 6 million, but because the company had set expectations by announcing a doubling of pre-orders from the year-ago 4S launch.

Instead of doubling its performance for the launch weekend the company only sold 25% more units. How can there be this discrepancy? Is this a sign that demand is not growing at the rate we’ve become accustomed to? Is it a sign that there are shortages of components or labor or other production problems?

No, probably none of the above.

What we saw in the 5 million figure is what the company was able to deliver in the hands of buyers. It’s possible that there were people who did not get a phone when they wanted it, and at the same time it’s possible that some phones were available for sale and did not get bought.

This is because Apple offers the product through multiple channels. Some channels like Apple Stores may have gotten too many units while other channels like their on-line store, operator stores or retail partners did not get enough.

In other words, we have a situation of over- and under-supply (or over- and under-demand) simultaneously because the product is misallocated.

Horace and Moisés discuss the early consumer response to iOS 6 (Maps in particular), and how people appear to greatly prefer native apps to their web app counterparts. They also dig into just how large an opportunity cost Apple is capable of absorbing in the interest of protecting their platform. In doing so, they examine the native app vs. HTML5 debate.

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With its recent release of the new Kindle Fire HD tablets, some have argued that Amazon has declared war on Apple and its iPad. But how serious is the threat? Are the two companies even playing the same game? I reached out to analyst Horace Dediu, founder and author of Asymco, to get his take. Dediu will speak on all this and more at TOC Frankfurt on October 9, 2012. Our short interview follows.

Matteo Fumagalli is a student of economics at University of Insubria, Italy. He is writing a thesis for a bachelor’s degree analyzing the smartphone industry.

He asked me to answer the following questions:

-First question is about you. Why did you found Asymco?

I founded the company to develop software, mainly apps. I began writing the blog as a way to drive traffic to the site. I would have preferred to build a blog only but did not think it was possible to earn any money doing that so I treated it as a hobby. Even after the site became more visible I changed from development to consulting and did not expect that writing in itself could be self-sustaining. It took about two years before I felt comfortable with the idea that I could do writing and speaking exclusively. I am still exploring additional business models however.

-You worked 8 years as analyst and business development manager at Nokia and you anticipated their current crisis with your first post on Asymco. Do you think Nokia will have the chance to recuperate, and eventually what will be the role of Windows Phone?

Nokia may recover or remain independent, at least. But it will be far smaller. The idea of a return to dominance or 40% share seems very unlikely. As I pointed out in the first post, the organization cannot cope with the new marketplace. Large organizations require extreme stress and damage to change. It’s a phenomenon at all levels of society that success results in rigidity. From the individual to the nation to the civilization, success makes change very, very difficult.

Windows Phone is an attempt to create a third ecosystem. I am concerned that the logic of having a third alternative is not solving a consumer need but an operator need. In other words, consumers are not asking for a third option and when they are presented with a third option they are not excited by it. The consumer does not think in terms of increasing their options. They decide once every two years which phone to buy and that is the end of their thinking on the subject. By focusing on the operator’s needs the platform is fundamentally mis-positioned.

What Windows Phone needs to be positioned as is either as fundamentally different, solving a different job for the consumer. Or fundamentally better along a new dimension like price or convenience. These are some of the claims it makes but they are very weak claims right now.

-What about RIM, other company which is going through difficult times? What do you think about their decision not to move to Android and stake everything on their closed OS?

We don’t want to just make a new phone. We want to make a much better phone.

– Jony Ive, video at iPhone 5 launch event

Disruption theory has taught us that the greatest danger facing a company is making a product better than it needs to be. There are numerous incentives for making products better but few incentives to re-directing improvements away from the prevailing basis of competition.

This danger is more acute for technology companies. Coupling incentives with the speed of improvement in various technologies (aka Moore’s law) means that over-service can come suddenly and more quickly than warnings from the marketplace. A product can tip from under- to over-shooting the market within one product cycle. One year the product is under-performing and trying to catch up to the competition and the next it’s superfluous and commoditized. The dilemma is compounded by the cycle time of development which can span multiple product cycles.

Therefore, how to tell whether a product is over-serving a market is one of the most important and frequently asked questions I get asked. It’s easy to see over-service in the rear view mirror when looking at a multi-year pattern. The trouble is that by the time you see the data, it’s too late. How do you tell you’re on the cusp of good enough, subject to imminent disruption before you get there?

I consider measuring a product’s absorbability to be a marketing problem. The marketer’s job is to read the signals from the market[1]. Determining absorbability comes down to reading two market signals, both of which must be met before green-lighting an improvement: (a) a product’s improvements must be used and (b) a product’s improvements must be valued.

If a product’s improvements are not used and the buyer will not pay more for them then they are not being absorbed and the effort to develop the improvements should be redirected.

Now the problem becomes one of measurement. Of the two, utilization is easier. Data can be gathered on whether a feature is being used. Research methods exist to tell if a feature would be used even if it’s not available[2]

The more difficult assessment is that of the value of a feature. You can usually only tell value by trying to price it and watching what happens. For example, you add more speed/memory/capacity and try charging more (or the same) for the product. The acceptance will be measured by sales growth and will give you an indication of whether these improvements are valuable.

If you have to add features and drop prices at the same time then it’s likely that the market does not value the improvement.

But this is extremely risky. You need to wait through a sales cycle and iterate through a development cycle before you have an answer. In a space where competitors are placing opposite bets, the experiment fails even if you get the data.

How can you structure a value measurement experiment without wasting an opportunity?

Rather than dealing with hypotheticals, let’s use the iPhone as a test case. As Jony Ive states, the focus for the latest iPhone was to make it better. Is this improvement absorbable? What happens if Apple’s bet on being better is wrong?

First, we can confirm that the iPhone has been on a trajectory of getting better and that those improvements have been absorbed so far. We can measure the history of performance of the product (roughly doubling every year) and we can also measure proxies for performance as I have in the following charts: